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Record W7017977013

Charles Denney and Wahkootowin: How a Populist Genealogist Inadvertently Shaped Metis Identity in Western Archives, 1967-2002

2025· other· en· W7017977013 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2025
Typeother
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsMetisIndigenousAgency (philosophy)Identity (music)Colonialism
DOInot available

Abstract

fetched live from OpenAlex

This dissertation investigates the genealogical collection held at the Glenbow Archives in Calgary. Curated by Edmonton genealogist Charles Denney and collected from the mid-1960s up until his death in 2002, the collection documented the genealogical data of Metis families. The Denney collection is not merely a repository of information. It actively contributes to the construction of contemporary Metis identities. Denney’s collection began with documenting his Metis wife Mildred Sherlock’s family history. The collection changed through Denney’s ‘kitchen table’ collaborations with Metis genealogists Clarence Kipling and Pat McCloy, its purchase by the Glenbow archives, and the use of the Denney collection by the Metis Nation to pursue wahkootowin (relatedness) and post-Powley section 35 rights. By critically engaging with genealogical records, this dissertation concludes that Denney’s archive was guided by the Metis concept of wahkootowin. Although these genealogies originated in a colonial concept of white-pioneer narratives, they have transformed into an act of Metis agency that asserts Metis identities and sovereignty. This study emphasizes the importance of understanding the creation and curation of archival collections and their impact on the recognition and preservation of Indigenous worldviews.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.676
Threshold uncertainty score0.645

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0400.029
Scholarly communication0.0140.008
Open science0.0010.008
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.197
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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